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Emerging Issues Analysis×Trend Impact Analysis×
분야Futures Foresight StudiesFutures Foresight Studies
계열Process / pipelineProcess / pipeline
기원 연도20091972
창시자Graham T. T. Molitor; Hawai'i School / Millennium ProjectTheodore J. Gordon (The Futures Group / Millennium Project)
유형Early-detection pipeline for issues on the S-curve of public attentionProbabilistic trend-extrapolation pipeline perturbed by future events
원전Glenn, J. C., & Gordon, T. J. (Eds.). (2009). Futures Research Methodology, Version 3.0. The Millennium Project. ISBN: 9780981894119Gordon, T. J., & Hayward, H. (1968). Initial experiments with the cross-impact matrix method of forecasting. Futures, 1(2), 100-116. DOI ↗
별칭Emerging Issue Analysis, EIA, Issues Emergence Analysis, Weak Signal ScanningTIA, Trend-Impact Forecasting, Probabilistic Trend Perturbation, Event-Adjusted Trend Extrapolation
관련33
요약Emerging Issues Analysis (EIA) is a horizon-scanning method, associated with Graham Molitor and the Hawai'i School and codified in the Millennium Project's Futures Research Methodology, for detecting issues at the earliest, weakest-signal stage — long before they register as trends or reach public consciousness. Its organizing idea is that issues, like technologies, follow an S-curve of public attention: they begin in obscure, marginal sources, accelerate as advocates and specialists pick them up, and only later become widely recognized trends and finally mainstream concerns. The strategic value of catching an issue on the flat, early part of that curve is enormous, because that is when there is the most time and the most room to respond. EIA therefore deliberately scans the fringe — specialist literature, activist publications, patents, subcultures, marginal voices — to spot the small clouds on the horizon and position them on the issue lifecycle.Trend impact analysis (TIA) is a forecasting method that marries quantitative extrapolation with expert judgment about disruptive future events. Developed by Theodore Gordon and colleagues at The Futures Group in the early 1970s and later codified in the Millennium Project's Futures Research Methodology, it starts from a 'surprise-free' baseline produced by fitting and projecting a historical time series. It then asks which unprecedented events — events with no historical analog that ordinary extrapolation cannot anticipate — could deflect that trend, and with what probability, magnitude, and timing. Through Monte Carlo simulation those probabilistic impacts perturb the baseline, yielding not a single line but a probability envelope that shows how the trend might bend if the unexpected occurs.
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